1 code implementation • COLING 2022 • João António Rodrigues, António Branco
Relevant to all application domains where it is important to get at the reasons underlying sentiments and decisions, argument mining seeks to obtain structured arguments from unstructured text and has been addressed by approaches typically involving some feature and/or neural architecture engineering.
1 code implementation • GWC 2019 • Ruben Branco, João Rodrigues, Chakaveh Saedi, António Branco
An effective conversion method was proposed in the literature to obtain a lexical semantic space from a lexical semantic graph, thus permitting to obtain WordNet embeddings from WordNets.
no code implementations • GWC 2018 • Tomasz Naskręt, Agnieszka Dziob, Maciej Piasecki, Chakaveh Saedi, António Branco
The paper presents a new re-built and expanded, version 2. 0 of WordnetLoom – an open wordnet editor.
1 code implementation • MMMPIE (COLING) 2022 • Rodrigo Santos, António Branco, João Ricardo Silva
Cross-modal language and image processing is envisaged as a way to improve language understanding by resorting to visual grounding, but only recently, with the emergence of neural architectures specifically tailored to cope with both modalities, has it attracted increased attention and obtained promising results.
1 code implementation • EMNLP 2021 • Ruben Branco, António Branco, João António Rodrigues, João Ricardo Silva
Commonsense is a quintessential human capacity that has been a core challenge to Artificial Intelligence since its inception.
1 code implementation • LREC 2022 • António Branco, João Ricardo Silva, Luís Gomes, João António Rodrigues
This paper presents a new collection of quality language resources for the computational processing of the Portuguese language under the Universal Dependencies framework (UD).
no code implementations • 8 Apr 2024 • Tomás Osório, Bernardo Leite, Henrique Lopes Cardoso, Luís Gomes, João Rodrigues, Rodrigo Santos, António Branco
Similarly, the respective fine-tuned neural language models, developed with a low-rank adaptation approach, are made available as baselines that can stimulate future work on the neural processing of Portuguese.
no code implementations • 12 Mar 2024 • Rodrigo Santos, João Silva, António Branco
The combination of language processing and image processing keeps attracting increased interest given recent impressive advances that leverage the combined strengths of both domains of research.
no code implementations • 4 Mar 2024 • Rodrigo Santos, João Rodrigues, Luís Gomes, João Silva, António Branco, Henrique Lopes Cardoso, Tomás Freitas Osório, Bernardo Leite
To foster the neural encoding of Portuguese, this paper contributes foundation encoder models that represent an expansion of the still very scarce ecosystem of large language models specifically developed for this language that are fully open, in the sense that they are open source and openly distributed for free under an open license for any purpose, thus including research and commercial usages.
no code implementations • 29 Feb 2024 • Rodrigo Santos, João Silva, Luís Gomes, João Rodrigues, António Branco
To advance the neural decoding of Portuguese, in this paper we present a fully open Transformer-based, instruction-tuned decoder model that sets a new state of the art in this respect.
no code implementations • 11 May 2023 • João Rodrigues, Luís Gomes, João Silva, António Branco, Rodrigo Santos, Henrique Lopes Cardoso, Tomás Osório
To advance the neural encoding of Portuguese (PT), and a fortiori the technological preparation of this language for the digital age, we developed a Transformer-based foundation model that sets a new state of the art in this respect for two of its variants, namely European Portuguese from Portugal (PT-PT) and American Portuguese from Brazil (PT-BR).
no code implementations • 6 Sep 2022 • João Rodrigues, Ruben Branco, António Branco
Experimental results show that transfer learning techniques are beneficial to the task and that current methods may be insufficient to leverage commonsense knowledge from different lexical semantic families.
no code implementations • 11 Mar 2021 • António Branco
This paper provides an integrated overview of these constraints holding on the pairing of nominal anaphors with their admissible antecedents that are based on grammatical relations and structure.
no code implementations • COLING 2020 • António Branco, João Rodrigues, Małgorzata Salawa, Ruben Branco, Chakaveh Saedi
Lexical semantics theories differ in advocating that the meaning of words is represented as an inference graph, a feature mapping or a vector space, thus raising the question: is it the case that one of these approaches is superior to the others in representing lexical semantics appropriately?
no code implementations • LREC 2020 • Georg Rehm, Katrin Marheinecke, Stefanie Hegele, Stelios Piperidis, Kalina Bontcheva, Jan Hajič, Khalid Choukri, Andrejs Vasiļjevs, Gerhard Backfried, Christoph Prinz, José Manuel Gómez Pérez, Luc Meertens, Paul Lukowicz, Josef van Genabith, Andrea Lösch, Philipp Slusallek, Morten Irgens, Patrick Gatellier, Joachim köhler, Laure Le Bars, Dimitra Anastasiou, Albina Auksoriūtė, Núria Bel, António Branco, Gerhard Budin, Walter Daelemans, Koenraad De Smedt, Radovan Garabík, Maria Gavriilidou, Dagmar Gromann, Svetla Koeva, Simon Krek, Cvetana Krstev, Krister Lindén, Bernardo Magnini, Jan Odijk, Maciej Ogrodniczuk, Eiríkur Rögnvaldsson, Mike Rosner, Bolette Sandford Pedersen, Inguna Skadiņa, Marko Tadić, Dan Tufiş, Tamás Váradi, Kadri Vider, Andy Way, François Yvon
Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality.
no code implementations • 2 Dec 2019 • Tao Wang, Shaohui Kuang, Deyi Xiong, António Branco
As neural machine translation (NMT) is not easily amenable to explicit correction of errors, incorporating pre-specified translations into NMT is widely regarded as a non-trivial challenge.
no code implementations • ACL 2018 • Shaohui Kuang, Junhui Li, António Branco, Weihua Luo, Deyi Xiong
In neural machine translation, a source sequence of words is encoded into a vector from which a target sequence is generated in the decoding phase.